Chatbots
A conversational agent, or chatbot, is a computer program that uses artificial intelligence to simulate a conversation with users. It can interact via text or voice, answering questions, providing information, or carrying out simple tasks. Chatbots are commonly embedded in websites, apps, and messaging platforms.
Background and origins
The history of chatbots goes back to the 1960s with ELIZA (MIT), an early rule-based system mimicking a psychotherapist, and later ALICE in the 1990s. Early bots relied on scripted patterns, but the development of natural language processing (NLP) and deep learning enabled more advanced conversational agents. Today, large language models (LLMs) such as GPT power sophisticated chatbots that can handle nuanced and context-rich dialogues.
Practical applications
- Customer service: answering FAQs, reducing wait times.
- E-commerce: guiding users through purchases and making recommendations.
- Healthcare: providing general medical information or triaging patients.
- Education: interactive tutoring and personalized learning support.
- Enterprise tools: internal assistants for employee support and knowledge access.
Challenges, limitations or debates
- Accuracy and reliability: chatbots may give wrong or incomplete answers.
- Bias and fairness: AI-powered agents risk reflecting stereotypes or biases in training data.
- Privacy concerns: conversations may be logged and analyzed.
- User acceptance: in sensitive areas, people may still prefer human interaction.
Conversational agents can be seen as the frontline ambassadors of AI, translating complex technologies into everyday interactions. What makes them powerful is not only their ability to provide information but also to create an illusion of natural dialogue. With modern LLMs, chatbots are increasingly able to manage context across turns, personalize responses, and even detect sentiment to adapt their tone.
From a business perspective, chatbots are valuable because they scale conversations. A single bot can handle thousands of simultaneous queries, something impossible for human staff. At the same time, hybrid systems—where bots handle routine questions and seamlessly hand off complex cases to humans—are becoming a best practice to ensure both efficiency and quality.
Still, challenges remain. Current chatbots can hallucinate answers, offering confident but incorrect information, which is problematic in domains like medicine or law. Ethical debates also continue around transparency: should users always be explicitly told when they are speaking with a bot? These discussions highlight that conversational agents are not just technical artifacts but also social actors shaping how people interact with machines.
References
- Wikipedia – Conversational agent
- Weizenbaum, J. (1966). ELIZA. MIT.
- Stanford HAI – Conversational AI
